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Anti-phase cocontraction practice attenuates in-phase low-frequency oscillations between antagonistic muscles as assessed with phase coherence

  • Nayef E. Ahmar
  • Jun Ueda
  • Minoru ShinoharaEmail author
Research Article

Abstract

Voluntary contraction of skeletal muscles involves common in-phase neural oscillations in low frequencies (around 1–2 Hz) across muscles. The purpose of this study was to determine if anti-phase antagonistic cocontraction practice can attenuate the occurrence of in-phase low-frequency oscillations in antagonistic muscle activity. For this purpose, we determined the probability density function of phase coherence in surface electromyogram (EMG) between antagonistic muscles. Healthy young adults were assigned to one of three intervention groups. They performed an isometric transient and steady cocontraction test with elbow flexors and extensors before and after a session of distinct intervention. In the Cocontraction group, subjects practiced alternating anti-phase isometric cocontraction with the flexors and extensors concurrently. In the Contraction group, subjects practiced alternating isometric contraction levels with flexors or extensors independently. Subjects in the Control group did not perform motor practice. The occurrence of in-phase coherence < 3 Hz during the cocontraction test (including transient and steady portions) was determined from the probability density function of phase coherence in rectified EMG between pairs of elbow flexor and extensor muscles. The change in the probability of in-phase coherence after the intervention period was greatest in the Cocontraction group, followed by Contraction group, and then Control group, on average. The Cocontraction group showed significantly greater reductions than the Control group across the cocontraction test portions. The results suggest that a session of anti-phase cocontraction practice can consistently attenuate the occurrence of in-phase low-frequency oscillations between cocontracting antagonistic muscles across steady and non-steady cocontractions in healthy young adults.

Keywords

Antagonist Common drive Correlated oscillations EMG Muscle coactivation 

Notes

Acknowledgements

This material was supported, in part, by the National Science Foundation under Grant No. IIS 1317718. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

References

  1. Ahmar NE, Shinohara M (2017) Slow intermuscular oscillations are associated with cocontraction steadiness. Med Sci Sports Exerc 49:1955–1964CrossRefGoogle Scholar
  2. Asaka T, Yahata K, Mani H, Wang Y (2011) Modulations of muscle modes in automatic postural responses induced by external surface translations. J Mot Behav 43:165–172CrossRefGoogle Scholar
  3. De Luca CJ, Erim Z (1994) Common drive of motor units in regulation of muscle force. Trends Neurosci 17:299–305CrossRefGoogle Scholar
  4. De Luca CJ, Mambrito B (1987) Voluntary control of motor units in human antagonist muscles: coactivation and reciprocal activation. J Neurophysiol 58:525–542CrossRefGoogle Scholar
  5. De Luca CJ, LeFever RS, McCue MP, Xenakis AP (1982) Control scheme governing concurrently active human motor units during voluntary contractions. J Physiol 329:129–142CrossRefGoogle Scholar
  6. Delorme A, Makeig S (2004) EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134:9–21CrossRefGoogle Scholar
  7. Farina D, Negro F (2015) Common synaptic input to motor neurons, motor unit synchronization, and force control. Exerc Sport Sci Rev 43:23–33CrossRefGoogle Scholar
  8. Farina D, Merletti R, Enoka RM (2004) The extraction of neural strategies from the surface EMG. J Appl Physiol 96:1486–1495CrossRefGoogle Scholar
  9. Geertsen SS, Kjaer M, Pedersen KK, Petersen TH, Perez MA, Nielsen JB (2013) Central common drive to antagonistic ankle muscles in relation to short-term cocontraction training in nondancers and professional ballet dancers. J Appl Physiol 115:1075–1081CrossRefGoogle Scholar
  10. Glendinning DS, Enoka RM (1994) Motor unit behavior in Parkinson’s disease. Phys Ther 74:61–70CrossRefGoogle Scholar
  11. Holmes MR, Gould JR, Pena-Gonzalez I, Enoka RM (2015) Force steadiness during a co-contraction task can be improved with practice, but only by young adults and not by middle-aged or old adults. Exp Physiol 100:182–192CrossRefGoogle Scholar
  12. Krishnamoorthy V, Latash ML, Scholz JP, Zatsiorsky VM (2004) Muscle modes during shifts of the center of pressure by standing persons: effect of instability and additional support. Exp Brain Res 157:18–31CrossRefGoogle Scholar
  13. Mizuno Y, Tanaka R, Yanagisawa N (1971) Reciprocal group I inhibition on triceps surae motoneurons in man. J Neurophysiol 34:1010–1017CrossRefGoogle Scholar
  14. Negro F, Holobar A, Farina D (2009) Fluctuations in isometric muscle force can be described by one linear projection of low-frequency components of motor unit discharge rates. J Physiol 587:5925–5938CrossRefGoogle Scholar
  15. Negro F, Keenan K, Farina D (2015) Power spectrum of the rectified EMG: when and why is rectification beneficial for identifying neural connectivity? J Neural Eng 12:036008CrossRefGoogle Scholar
  16. Negro F, Yavuz US, Farina D (2016) The human motor neuron pools receive a dominant slow-varying common synaptic input. J Physiol 594:5491–5505CrossRefGoogle Scholar
  17. Patel H, O’Neill G, Artemiadis P (2014) On the effect of muscular cocontraction on the 3-D human arm impedance. IEEE Trans Biomed Eng 61:2602–2608CrossRefGoogle Scholar
  18. Perez MA, Lundbye-Jensen J, Nielsen JB (2007) Task-specific depression of the soleus H-reflex after cocontraction training of antagonistic ankle muscles. J Neurophysiol 98:3677–3687CrossRefGoogle Scholar
  19. Ueda J, Gallagher W, Moualeu A, Shinohara M, Feigh K (2016) Adaptive human–robot physical interaction for robot coworkers. In: Ueda J, Kurita Y (eds) Human modelling for bio-inspired robotics. Elsevier, New York, pp 297–333Google Scholar
  20. Unnithan VB, Dowling JJ, Frost G, Bar-Or O (1996) Role of cocontraction in the O2 cost of walking in children with cerebral palsy. Med Sci Sports Exerc 28:1498–1504CrossRefGoogle Scholar
  21. Yamagata M, Falaki A, Latash ML (2019) Effects of voluntary agonist-antagonist coactivation on stability of vertical posture. Mot Control 23:304–326CrossRefGoogle Scholar
  22. Yoshitake Y, Shinohara M (2013) Oscillations in motor unit discharge are reflected in the low-frequency component of rectified surface EMG and the rate of change in force. Exp Brain Res 231:267–276CrossRefGoogle Scholar
  23. Yoshitake Y, Kanehisa H, Shinohara M (2017) Correlated EMG oscillations between antagonists during cocontraction in men. Med Sci Sports Exerc 49:538–548CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.George W. Woodruff School of Mechanical EngineeringGeorgia Institute of TechnologyAtlantaUSA
  3. 3.School of Biological SciencesGeorgia Institute of TechnologyAtlantaUSA

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